Publications by authors named "Jason L Stein"

78 Publications

Common genetic variation influencing human white matter microstructure.

Science 2021 06;372(6548)

Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

Brain regions communicate with each other through tracts of myelinated axons, commonly referred to as white matter. We identified common genetic variants influencing white matter microstructure using diffusion magnetic resonance imaging of 43,802 individuals. Genome-wide association analysis identified 109 associated loci, 30 of which were detected by tract-specific functional principal components analysis. A number of loci colocalized with brain diseases, such as glioma and stroke. Genetic correlations were observed between white matter microstructure and 57 complex traits and diseases. Common variants associated with white matter microstructure altered the function of regulatory elements in glial cells, particularly oligodendrocytes. This large-scale tract-specific study advances the understanding of the genetic architecture of white matter and its genetic links to a wide spectrum of clinical outcomes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1126/science.abf3736DOI Listing
June 2021

Segmentor: a tool for manual refinement of 3D microscopy annotations.

BMC Bioinformatics 2021 May 22;22(1):260. Epub 2021 May 22.

UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Drive, CB# 7250, Chapel Hill, NC, 27599, USA.

Background: Recent advances in tissue clearing techniques, combined with high-speed image acquisition through light sheet microscopy, enable rapid three-dimensional (3D) imaging of biological specimens, such as whole mouse brains, in a matter of hours. Quantitative analysis of such 3D images can help us understand how changes in brain structure lead to differences in behavior or cognition, but distinguishing densely packed features of interest, such as nuclei, from background can be challenging. Recent deep learning-based nuclear segmentation algorithms show great promise for automated segmentation, but require large numbers of accurate manually labeled nuclei as training data.

Results: We present Segmentor, an open-source tool for reliable, efficient, and user-friendly manual annotation and refinement of objects (e.g., nuclei) within 3D light sheet microscopy images. Segmentor employs a hybrid 2D-3D approach for visualizing and segmenting objects and contains features for automatic region splitting, designed specifically for streamlining the process of 3D segmentation of nuclei. We show that editing simultaneously in 2D and 3D using Segmentor significantly decreases time spent on manual annotations without affecting accuracy as compared to editing the same set of images with only 2D capabilities.

Conclusions: Segmentor is a tool for increased efficiency of manual annotation and refinement of 3D objects that can be used to train deep learning segmentation algorithms, and is available at https://www.nucleininja.org/ and https://github.com/RENCI/Segmentor .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12859-021-04202-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8141214PMC
May 2021

Cell-type-specific effects of genetic variation on chromatin accessibility during human neuronal differentiation.

Nat Neurosci 2021 Jul 20;24(7):941-953. Epub 2021 May 20.

Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Common genetic risk for neuropsychiatric disorders is enriched in regulatory elements active during cortical neurogenesis. However, it remains poorly understood as to how these variants influence gene regulation. To model the functional impact of common genetic variation on the noncoding genome during human cortical development, we performed the assay for transposase accessible chromatin using sequencing (ATAC-seq) and analyzed chromatin accessibility quantitative trait loci (QTL) in cultured human neural progenitor cells and their differentiated neuronal progeny from 87 donors. We identified significant genetic effects on 988/1,839 neuron/progenitor regulatory elements, with highly cell-type and temporally specific effects. A subset (roughly 30%) of chromatin accessibility-QTL were also associated with changes in gene expression. Motif-disrupting alleles of transcriptional activators generally led to decreases in chromatin accessibility, whereas motif-disrupting alleles of repressors led to increases in chromatin accessibility. By integrating cell-type-specific chromatin accessibility-QTL and brain-relevant genome-wide association data, we were able to fine-map and identify regulatory mechanisms underlying noncoding neuropsychiatric disorder risk loci.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41593-021-00858-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254789PMC
July 2021

From base pair to brain.

Nat Neurosci 2021 05;24(5):619-621

Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41593-021-00852-2DOI Listing
May 2021

MRLocus: Identifying causal genes mediating a trait through Bayesian estimation of allelic heterogeneity.

PLoS Genet 2021 Apr 19;17(4):e1009455. Epub 2021 Apr 19.

Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.

Expression quantitative trait loci (eQTL) studies are used to understand the regulatory function of non-coding genome-wide association study (GWAS) risk loci, but colocalization alone does not demonstrate a causal relationship of gene expression affecting a trait. Evidence for mediation, that perturbation of gene expression in a given tissue or developmental context will induce a change in the downstream GWAS trait, can be provided by two-sample Mendelian Randomization (MR). Here, we introduce a new statistical method, MRLocus, for Bayesian estimation of the gene-to-trait effect from eQTL and GWAS summary data for loci with evidence of allelic heterogeneity, that is, containing multiple causal variants. MRLocus makes use of a colocalization step applied to each nearly-LD-independent eQTL, followed by an MR analysis step across eQTLs. Additionally, our method involves estimation of the extent of allelic heterogeneity through a dispersion parameter, indicating variable mediation effects from each individual eQTL on the downstream trait. Our method is evaluated against other state-of-the-art methods for estimation of the gene-to-trait mediation effect, using an existing simulation framework. In simulation, MRLocus often has the highest accuracy among competing methods, and in each case provides more accurate estimation of uncertainty as assessed through interval coverage. MRLocus is then applied to five candidate causal genes for mediation of particular GWAS traits, where gene-to-trait effects are concordant with those previously reported. We find that MRLocus's estimation of the causal effect across eQTLs within a locus provides useful information for determining how perturbation of gene expression or individual regulatory elements will affect downstream traits. The MRLocus method is implemented as an R package available at https://mikelove.github.io/mrlocus.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.pgen.1009455DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084342PMC
April 2021

Ten years of enhancing neuro-imaging genetics through meta-analysis: An overview from the ENIGMA Genetics Working Group.

Hum Brain Mapp 2020 Dec 10. Epub 2020 Dec 10.

Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, California, USA.

Here we review the motivation for creating the enhancing neuroimaging genetics through meta-analysis (ENIGMA) Consortium and the genetic analyses undertaken by the consortium so far. We discuss the methodological challenges, findings, and future directions of the genetics working group. A major goal of the working group is tackling the reproducibility crisis affecting "candidate gene" and genome-wide association analyses in neuroimaging. To address this, we developed harmonized analytic methods, and support their use in coordinated analyses across sites worldwide, which also makes it possible to understand heterogeneity in results across sites. These efforts have resulted in the identification of hundreds of common genomic loci robustly associated with brain structure. We have found both pleiotropic and specific genetic effects associated with brain structures, as well as genetic correlations with psychiatric and neurological diseases.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/hbm.25311DOI Listing
December 2020

The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area.

Cereb Cortex 2021 Mar;31(4):1873-1887

Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.

Structural brain changes along the lineage leading to modern Homo sapiens contributed to our distinctive cognitive and social abilities. However, the evolutionarily relevant molecular variants impacting key aspects of neuroanatomy are largely unknown. Here, we integrate evolutionary annotations of the genome at diverse timescales with common variant associations from large-scale neuroimaging genetic screens. We find that alleles with evidence of recent positive polygenic selection over the past 2000-3000 years are associated with increased surface area (SA) of the entire cortex, as well as specific regions, including those involved in spoken language and visual processing. Therefore, polygenic selective pressures impact the structure of specific cortical areas even over relatively recent timescales. Moreover, common sequence variation within human gained enhancers active in the prenatal cortex is associated with postnatal global SA. We show that such variation modulates the function of a regulatory element of the developmentally relevant transcription factor HEY2 in human neural progenitor cells and is associated with structural changes in the inferior frontal cortex. These results indicate that non-coding genomic regions active during prenatal cortical development are involved in the evolution of human brain structure and identify novel regulatory elements and genes impacting modern human brain structure.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/cercor/bhaa327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7945014PMC
March 2021

Evaluating brain structure traits as endophenotypes using polygenicity and discoverability.

Hum Brain Mapp 2020 Oct 24. Epub 2020 Oct 24.

Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Human brain structure traits have been hypothesized to be broad endophenotypes for neuropsychiatric disorders, implying that brain structure traits are comparatively "closer to the underlying biology." Genome-wide association studies from large sample sizes allow for the comparison of common variant genetic architectures between traits to test the evidence supporting this claim. Endophenotypes, compared to neuropsychiatric disorders, are hypothesized to have less polygenicity, with greater effect size of each susceptible SNP, requiring smaller sample sizes to discover them. Here, we compare polygenicity and discoverability of brain structure traits, neuropsychiatric disorders, and other traits (91 in total) to directly test this hypothesis. We found reduced polygenicity (FDR = 0.01) and increased discoverability (FDR = 3.68 × 10 ) of cortical brain structure traits, as compared to aggregated estimates of multiple neuropsychiatric disorders. We predict that ~8 M individuals will be required to explain the full heritability of cortical surface area by genome-wide significant SNPs, whereas sample sizes over 20 M will be required to explain the full heritability of depression. In conclusion, our findings are consistent with brain structure satisfying the higher power criterion of endophenotypes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/hbm.25257DOI Listing
October 2020

Cas9 gene therapy for Angelman syndrome traps Ube3a-ATS long non-coding RNA.

Nature 2020 11 21;587(7833):281-284. Epub 2020 Oct 21.

UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Angelman syndrome (AS) is a severe neurodevelopmental disorder caused by a mutation or deletion of the maternally inherited UBE3A allele. In neurons, the paternally inherited UBE3A allele is silenced in cis by a long non-coding RNA called UBE3A-ATS. Here, as part of a systematic screen, we found that Cas9 can be used to activate ('unsilence') paternal Ube3a in cultured mouse and human neurons when targeted to Snord115 genes, which are small nucleolar RNAs that are clustered in the 3' region of Ube3a-ATS. A short Cas9 variant and guide RNA that target about 75 Snord115 genes were packaged into an adeno-associated virus and administered to a mouse model of AS during the embryonic and early postnatal stages, when the therapeutic benefit of restoring Ube3a is predicted to be greatest. This early treatment unsilenced paternal Ube3a throughout the brain for at least 17 months and rescued anatomical and behavioural phenotypes in AS mice. Genomic integration of the adeno-associated virus vector into Cas9 target sites caused premature termination of Ube3a-ATS at the vector-derived polyA cassette, or when integrated in the reverse orientation, by transcriptional collision with the vector-derived Cas9 transcript. Our study shows that targeted genomic integration of a gene therapy vector can restore the function of paternally inherited UBE3A throughout life, providing a path towards a disease-modifying treatment for a syndromic neurodevelopmental disorder.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41586-020-2835-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8020672PMC
November 2020

Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults.

Nat Commun 2020 09 22;11(1):4796. Epub 2020 Sep 22.

Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-18367-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508833PMC
September 2020

Common genetic risk variants identified in the SPARK cohort support DDHD2 as a candidate risk gene for autism.

Transl Psychiatry 2020 08 3;10(1):265. Epub 2020 Aug 3.

Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder. Large genetically informative cohorts of individuals with ASD have led to the identification of a limited number of common genome-wide significant (GWS) risk loci to date. However, many more common genetic variants are expected to contribute to ASD risk given the high heritability. Here, we performed a genome-wide association study (GWAS) on 6222 case-pseudocontrol pairs from the Simons Foundation Powering Autism Research for Knowledge (SPARK) dataset to identify additional common genetic risk factors and molecular mechanisms underlying risk for ASD. We identified one novel GWS locus from the SPARK GWAS and four significant loci, including an additional novel locus from meta-analysis with a previous GWAS. We replicated the previous observation of significant enrichment of ASD heritability within regulatory regions of the developing cortex, indicating that disruption of gene regulation during neurodevelopment is critical for ASD risk. We further employed a massively parallel reporter assay (MPRA) and identified a putative causal variant at the novel locus from SPARK GWAS with strong impacts on gene regulation (rs7001340). Expression quantitative trait loci data demonstrated an association between the risk allele and decreased expression of DDHD2 (DDHD domain containing 2) in both adult and prenatal brains. In conclusion, by integrating genetic association data with multi-omic gene regulatory annotations and experimental validation, we fine-mapped a causal risk variant and demonstrated that DDHD2 is a novel gene associated with ASD risk.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41398-020-00953-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400671PMC
August 2020

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

Transl Psychiatry 2020 03 20;10(1):100. Epub 2020 Mar 20.

Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41398-020-0705-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083923PMC
March 2020

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms.

Cell 2019 10;179(3):750-771.e22

Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, 695 Charles E. Young Drive South, Los Angeles, CA 90095, USA; Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, 695 Charles E. Young Drive South, Los Angeles, CA 90095, USA. Electronic address:

Tissue-specific regulatory regions harbor substantial genetic risk for disease. Because brain development is a critical epoch for neuropsychiatric disease susceptibility, we characterized the genetic control of the transcriptome in 201 mid-gestational human brains, identifying 7,962 expression quantitative trait loci (eQTL) and 4,635 spliceQTL (sQTL), including several thousand prenatal-specific regulatory regions. We show that significant genetic liability for neuropsychiatric disease lies within prenatal eQTL and sQTL. Integration of eQTL and sQTL with genome-wide association studies (GWAS) via transcriptome-wide association identified dozens of novel candidate risk genes, highlighting shared and stage-specific mechanisms in schizophrenia (SCZ). Gene network analysis revealed that SCZ and autism spectrum disorder (ASD) affect distinct developmental gene co-expression modules. Yet, in each disorder, common and rare genetic variation converges within modules, which in ASD implicates superficial cortical neurons. More broadly, these data, available as a web browser and our analyses, demonstrate the genetic mechanisms by which developmental events have a widespread influence on adult anatomical and behavioral phenotypes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cell.2019.09.021DOI Listing
October 2019

A Single-Cell Transcriptomic Atlas of Human Neocortical Development during Mid-gestation.

Neuron 2019 09 11;103(5):785-801.e8. Epub 2019 Jul 11.

Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA; Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA. Electronic address:

We performed RNA sequencing on 40,000 cells to create a high-resolution single-cell gene expression atlas of developing human cortex, providing the first single-cell characterization of previously uncharacterized cell types, including human subplate neurons, comparisons with bulk tissue, and systematic analyses of technical factors. These data permit deconvolution of regulatory networks connecting regulatory elements and transcriptional drivers to single-cell gene expression programs, significantly extending our understanding of human neurogenesis, cortical evolution, and the cellular basis of neuropsychiatric disease. We tie cell-cycle progression with early cell fate decisions during neurogenesis, demonstrating that differentiation occurs on a transcriptomic continuum; rather than only expressing a few transcription factors that drive cell fates, differentiating cells express broad, mixed cell-type transcriptomes before telophase. By mapping neuropsychiatric disease genes to cell types, we implicate dysregulation of specific cell types in ASD, ID, and epilepsy. We developed CoDEx, an online portal to facilitate data access and browsing.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuron.2019.06.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6831089PMC
September 2019

Memo1-Mediated Tiling of Radial Glial Cells Facilitates Cerebral Cortical Development.

Neuron 2019 09 2;103(5):836-852.e5. Epub 2019 Jul 2.

UNC Neuroscience Center and the Department of Cell Biology and Physiology, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA. Electronic address:

Polarized, non-overlapping, regularly spaced, tiled organization of radial glial cells (RGCs) serves as a framework to generate and organize cortical neuronal columns, layers, and circuitry. Here, we show that mediator of cell motility 1 (Memo1) is a critical determinant of radial glial tiling during neocortical development. Memo1 deletion or knockdown leads to hyperbranching of RGC basal processes and disrupted RGC tiling, resulting in aberrant radial unit assembly and neuronal layering. Memo1 regulates microtubule (MT) stability necessary for RGC tiling. Memo1 deficiency leads to disrupted MT minus-end CAMSAP2 distribution, initiation of aberrant MT branching, and altered polarized trafficking of key basal domain proteins such as GPR56, and thus aberrant RGC tiling. These findings identify Memo1 as a mediator of RGC scaffold tiling, necessary to generate and organize neurons into functional ensembles in the developing cerebral cortex.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuron.2019.05.049DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728225PMC
September 2019

Mapping causal pathways from genetics to neuropsychiatric disorders using genome-wide imaging genetics: Current status and future directions.

Psychiatry Clin Neurosci 2019 Jul 21;73(7):357-369. Epub 2019 May 21.

Department of Genetics & UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA.

Imaging genetics aims to identify genetic variants associated with the structure and function of the human brain. Recently, collaborative consortia have been successful in this goal, identifying and replicating common genetic variants influencing gross human brain structure as measured through magnetic resonance imaging. In this review, we contextualize imaging genetic associations as one important link in understanding the causal chain from genetic variant to increased risk for neuropsychiatric disorders. We provide examples in other fields of how identifying genetic variant associations to disease and multiple phenotypes along the causal chain has revealed a mechanistic understanding of disease risk, with implications for how imaging genetics can be similarly applied. We discuss current findings in the imaging genetics research domain, including that common genetic variants can have a slightly larger effect on brain structure than on risk for disorders like schizophrenia, indicating a somewhat simpler genetic architecture. Also, gross brain structure measurements share a genetic basis with some, but not all, neuropsychiatric disorders, invalidating the previously held belief that they are broad endophenotypes, yet pinpointing brain regions likely involved in the pathology of specific disorders. Finally, we suggest that in order to build a more detailed mechanistic understanding of the effects of genetic variants on the brain, future directions in imaging genetics research will require observations of cellular and synaptic structure in specific brain regions beyond the resolution of magnetic resonance imaging. We expect that integrating genetic associations at biological levels from synapse to sulcus will reveal specific causal pathways impacting risk for neuropsychiatric disorders.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/pcn.12839DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6625892PMC
July 2019

Genetic Markers of ADHD-Related Variations in Intracranial Volume.

Am J Psychiatry 2019 03;176(3):228-238

The Department of Human Genetics, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands (Klein, Bralten, Roth Mota, Arias-Vasquez, Franke); University Medical Center Utrecht, UMC Utrecht Brain Center, Department of Psychiatry, Utrecht, the Netherlands (Klein); the Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston (Walters, Neale); Program in Medical and Population Genetics (Walters) and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Mass (Walters, Neale); the Department of Biomedicine and the Center for Integrative Sequencing, Aarhus University, Aarhus, Denmark (Demontis, Mattheisen, Børglum); the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Denmark (Demontis, Børglum); the Department of Genetics and the Neuroscience Center, University of North Carolina, Chapel Hill (Stein); the Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles (Hibar, Thompson); the Department of Epidemiology and the Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the Netherlands (Adams); the Department of Psychiatry and the Research Institute, Hospital for Sick Children, University of Toronto, Toronto (Schachar); the Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Sonuga-Barke); the Department of Psychiatry, Psychosomatics and Psychotherapy, University of Wuerzburg, Wuerzburg, Germany (Mattheisen); the Department of Clinical Neuroscience, Center for Psychiatric Research, Karolinska Institute, Stockholm (Mattheisen); Stockholm Health Care Services, Stockholm County Council, Stockholm (Mattheisen); the Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles (Thompson); the Quantitative Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Australia (Medland); the Department of Psychiatry and the Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, N.Y. (Faraone); the K.G. Jebsen Center for Neuropsychiatric Disorders, University of Bergen, Bergen, Norway (Faraone); and the Department of Psychiatry, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands (Roth Mota, Arias-Vasquez, Franke).

Objective: Attention deficit hyperactivity disorder (ADHD) is a common and highly heritable neurodevelopmental disorder with a complex pathophysiology. Intracranial volume (ICV) and volumes of the nucleus accumbens, amygdala, caudate nucleus, hippocampus, and putamen are smaller in people with ADHD compared with healthy individuals. The authors investigated the overlap between common genetic variation associated with ADHD risk and these brain volume measures to identify underlying biological processes contributing to the disorder.

Methods: The authors combined genome-wide association results from the largest available studies of ADHD (N=55,374) and brain volumes (N=11,221-24,704), using a set of complementary methods to investigate overlap at the level of global common variant genetic architecture and at the single variant level.

Results: Analyses revealed a significant negative genetic correlation between ADHD and ICV (r=-0.22). Meta-analysis of single variants revealed two significant loci of interest associated with both ADHD risk and ICV; four additional loci were identified for ADHD and volumes of the amygdala, caudate nucleus, and putamen. Exploratory gene-based and gene-set analyses in the ADHD-ICV meta-analytic data showed association with variation in neurite outgrowth-related genes.

Conclusions: This is the first genome-wide study to show significant genetic overlap between brain volume measures and ADHD, both on the global and the single variant level. Variants linked to smaller ICV were associated with increased ADHD risk. These findings can help us develop new hypotheses about biological mechanisms by which brain structure alterations may be involved in ADHD disease etiology.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1176/appi.ajp.2018.18020149DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780894PMC
March 2019

The Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis.

Cell 2018 01 4;172(1-2):289-304.e18. Epub 2018 Jan 4.

Neurogenetics Program, Department of Neurology, University of California, Los Angeles, Los Angeles, CA 90095, USA; Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA. Electronic address:

Non-coding regions comprise most of the human genome and harbor a significant fraction of risk alleles for neuropsychiatric diseases, yet their functions remain poorly defined. We created a high-resolution map of non-coding elements involved in human cortical neurogenesis by contrasting chromatin accessibility and gene expression in the germinal zone and cortical plate of the developing cerebral cortex. We link distal regulatory elements (DREs) to their cognate gene(s) together with chromatin interaction data and show that target genes of human-gained enhancers (HGEs) regulate cortical neurogenesis and are enriched in outer radial glia, a cell type linked to human cortical evolution. We experimentally validate the regulatory effects of predicted enhancers for FGFR2 and EOMES. We observe that common genetic variants associated with educational attainment, risk for neuropsychiatric disease, and intracranial volume are enriched within regulatory elements involved in cortical neurogenesis, demonstrating the importance of this early developmental process for adult human cognitive function.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cell.2017.12.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5924568PMC
January 2018

Default Patterning Produces Pan-cortical Glutamatergic and CGE/LGE-like GABAergic Neurons from Human Pluripotent Stem Cells.

Stem Cell Reports 2017 11 26;9(5):1463-1476. Epub 2017 Oct 26.

Department of Neurosciences, University of New Mexico-Health Science Center, Albuquerque, NM 87131, USA. Electronic address:

Default differentiation of human pluripotent stem cells has been promoted as a model of cortical development. In this study, a developmental transcriptome analysis of default-differentiated hPSNs revealed a gene expression program resembling in vivo CGE/LGE subpallial domains and GABAergic signaling. A combination of bioinformatic, functional, and immunocytochemical analysis further revealed that hPSNs consist of both cortical glutamatergic and CGE-like GABAergic neurons. This study provides a comprehensive characterization of the heterogeneous group of neurons produced by default differentiation and insight into future directed differentiation strategies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.stemcr.2017.09.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5831028PMC
November 2017

Novel genetic loci associated with hippocampal volume.

Nat Commun 2017 01 18;8:13624. Epub 2017 Jan 18.

Pennington Biomedical Research Center, Baton Rouge, Louisiana 70808, USA.

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (r=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ncomms13624DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5253632PMC
January 2017

Novel genetic loci underlying human intracranial volume identified through genome-wide association.

Nat Neurosci 2016 12 3;19(12):1569-1582. Epub 2016 Oct 3.

Brain Center Rudolf Magnus, Department of Psychiatry, UMC Utrecht, Utrecht, the Netherlands.

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρ = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (N = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/nn.4398DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5227112PMC
December 2016

Chromosome conformation elucidates regulatory relationships in developing human brain.

Nature 2016 10 19;538(7626):523-527. Epub 2016 Oct 19.

Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California Los Angeles, California 90095, USA.

Three-dimensional physical interactions within chromosomes dynamically regulate gene expression in a tissue-specific manner. However, the 3D organization of chromosomes during human brain development and its role in regulating gene networks dysregulated in neurodevelopmental disorders, such as autism or schizophrenia, are unknown. Here we generate high-resolution 3D maps of chromatin contacts during human corticogenesis, permitting large-scale annotation of previously uncharacterized regulatory relationships relevant to the evolution of human cognition and disease. Our analyses identify hundreds of genes that physically interact with enhancers gained on the human lineage, many of which are under purifying selection and associated with human cognitive function. We integrate chromatin contacts with non-coding variants identified in schizophrenia genome-wide association studies (GWAS), highlighting multiple candidate schizophrenia risk genes and pathways, including transcription factors involved in neurogenesis, and cholinergic signalling molecules, several of which are supported by independent expression quantitative trait loci and gene expression analyses. Genome editing in human neural progenitors suggests that one of these distal schizophrenia GWAS loci regulates FOXG1 expression, supporting its potential role as a schizophrenia risk gene. This work provides a framework for understanding the effect of non-coding regulatory elements on human brain development and the evolution of cognition, and highlights novel mechanisms underlying neuropsychiatric disorders.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/nature19847DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5358922PMC
October 2016

Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility.

Neuron 2016 06 12;90(5):969-83. Epub 2016 May 12.

Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. Electronic address:

Depression is a complex, heterogeneous disorder and a leading contributor to the global burden of disease. Most previous research has focused on individual brain regions and genes contributing to depression. However, emerging evidence in humans and animal models suggests that dysregulated circuit function and gene expression across multiple brain regions drive depressive phenotypes. Here, we performed RNA sequencing on four brain regions from control animals and those susceptible or resilient to chronic social defeat stress at multiple time points. We employed an integrative network biology approach to identify transcriptional networks and key driver genes that regulate susceptibility to depressive-like symptoms. Further, we validated in vivo several key drivers and their associated transcriptional networks that regulate depression susceptibility and confirmed their functional significance at the levels of gene transcription, synaptic regulation, and behavior. Our study reveals novel transcriptional networks that control stress susceptibility and offers fundamentally new leads for antidepressant drug discovery.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuron.2016.04.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896746PMC
June 2016

Advancing the understanding of autism disease mechanisms through genetics.

Nat Med 2016 Apr;22(4):345-61

Neurogenetics Program, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.

Progress in understanding the genetic etiology of autism spectrum disorders (ASD) has fueled remarkable advances in our understanding of its potential neurobiological mechanisms. Yet, at the same time, these findings highlight extraordinary causal diversity and complexity at many levels ranging from molecules to circuits and emphasize the gaps in our current knowledge. Here we review current understanding of the genetic architecture of ASD and integrate genetic evidence, neuropathology and studies in model systems with how they inform mechanistic models of ASD pathophysiology. Despite the challenges, these advances provide a solid foundation for the development of rational, targeted molecular therapies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5072455PMC
http://dx.doi.org/10.1038/nm.4071DOI Listing
April 2016

Early developmental gene enhancers affect subcortical volumes in the adult human brain.

Hum Brain Mapp 2016 May 18;37(5):1788-800. Epub 2016 Feb 18.

Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands.

Genome-wide association screens aim to identify common genetic variants contributing to the phenotypic variability of complex traits, such as human height or brain morphology. The identified genetic variants are mostly within noncoding genomic regions and the biology of the genotype-phenotype association typically remains unclear. In this article, we propose a complementary targeted strategy to reveal the genetic underpinnings of variability in subcortical brain volumes, by specifically selecting genomic loci that are experimentally validated forebrain enhancers, active in early embryonic development. We hypothesized that genetic variation within these enhancers may affect the development and ultimately the structure of subcortical brain regions in adults. We tested whether variants in forebrain enhancer regions showed an overall enrichment of association with volumetric variation in subcortical structures of >13,000 healthy adults. We observed significant enrichment of genomic loci that affect the volume of the hippocampus within forebrain enhancers (empirical P = 0.0015), a finding which robustly passed the adjusted threshold for testing of multiple brain phenotypes (cutoff of P < 0.0083 at an alpha of 0.05). In analyses of individual single nucleotide polymorphisms (SNPs), we identified an association upstream of the ID2 gene with rs7588305 and variation in hippocampal volume. This SNP-based association survived multiple-testing correction for the number of SNPs analyzed but not for the number of subcortical structures. Targeting known regulatory regions offers a way to understand the underlying biology that connects genotypes to phenotypes, particularly in the context of neuroimaging genetics. This biology-driven approach generates testable hypotheses regarding the functional biology of identified associations. Hum Brain Mapp 37:1788-1800, 2016. © 2016 Wiley Periodicals, Inc.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/hbm.23136DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883000PMC
May 2016